The world of customer experience (CX) has been already radically transformed by AI innovation, according to recent research that sheds light on the key AI tactics—from harmonization to data availability—giving certain CX leaders a competitive edge.

In a survey of 300 senior CX executives, jointly conducted by Oxford Economics and SAP, every respondent stated that they are currently running some form of AI in their organizations' CX functions. But having implemented AI is no longer what separates the organizations achieving return on investment (ROI) from the ones struggling to see measurable results, according to Matthew Reynolds, Senior Editor for Thought Leadership – Technology at Oxford Economics, who presented the research findings during a recent SAP webinar.  

Across the board, some barriers faced by respondents are consistent: data quality and compliance concerns, integration challenges, and a lack of internal expertise. One factor separating CX leaders from their peers, according to the research, is related to whether AI can access the data and processes it requires to accelerate organizations' desired outcomes. Across the majority of surveyed organizations, fragmented systems, disconnected data sources, and integration workarounds limit the inputs that AI tools can leverage, leaving many organizations stuck using AI for basic tasks or cycling through pilots that never scale.  

The SAP and Oxford Economics study, however, identified a small group of respondents—a segment it refers to as “leaders”—who are deriving dramatically different results from other organizations by investing in both platform harmonization and employee readiness. 

While only 25% of respondents describe their CX technology as "fully harmonized," CX leaders—as distinguished by their success in platform harmonization—are significantly more likely to have AI embedded directly into enterprise workflows, and the performance gap that creates is stark.  94% of these leaders call AI moderately or very effective in sales forecasting, versus 54% of non-leaders, while 100% of them see AI as either moderately or very effective in optimizing supply chain processes (versus 55% of non-leaders). These leaders also ranked "revenue" as AI’s most positive impact at twice the rate of their peers (44% versus 22%). 

From Chatbots to Agents  

The next frontier in CX will involve agentic AI: systems that act on information, orchestrating processes—like lead-to-cash, quote-to-order, and issue-to-resolution—that span multiple business functions simultaneously. Such orchestration requires agents to maintain access to inventory constraints, pricing logic, fulfillment timelines, and customer history in one shared source of truth. 

Most organizations aren’t there yet. Nearly half are still exploring their first agentic-AI use cases. But CX leaders are in a different position, with 28% having deployed agentic AI at scale—3.4 times the rate of their peers. These leaders rank workforce readiness and platform readiness as nearly equal prerequisites for AI success. "Tech infrastructure and employee readiness are two sides of the AI coin,” said Reynolds. But 23% of organizations are committing only minimal resources to training employees on the data and processes that those agents are working with.  

“There’s a back and forth that needs to happen, and that can be a little painful,” he noted. “It can be a little deflating at points. But getting through that first stage helps you figure out a process of how you can work across teams.” 

Leaders who went through that process early are now seeing the payoff, as 78% report moderate or significant value from agentic AI in customer retention, versus 44% of non-leaders. 

The Blueprint  

Reynolds outlined four priorities for organizations looking to close the gap.  

• First, make platform harmonization a board-level conversation. “Any AI tool needs to be able to connect important apps, processes, systems that move away from fragmentation towards that harmony,” he said. “From a CX standpoint, CRM is the central focus.”
• Second, move from pilots to scale deployment in areas where AI is already proving valuable. Sales forecasting, customer interaction management, and personalized marketing all showed large performance gaps between leaders and the rest of the field. Reynolds’s team found that transformation issues can arise throughout the AI implementation process, from pitch and validation through deployment and modification. “Finding the resources to carry out an AI transformation and getting the workforce to embrace new ways of working play significant roles in getting these efforts off the ground,” he said. Organizations that wait for perfect conditions don’t necessarily avoid those challenges—they just haven’t encountered them yet.
• Third, start with compliance. This might seem counterintuitive, but Reynolds pointed to compliance as a safe entry point for agentic deployment, in areas where agents can “insulate the business while also informing core business operations” and where, if something goes wrong, “nothing catastrophic happens.” The data supports this logic: leaders report industry-leading AI maturity in compliance at rates far beyond their peers (53% versus 8%).
• Fourth, measure broadly. “You need to have a long list of KPIs,” Reynolds said. “AI can take value in many forms.” Integrated infrastructure tends to surface value where organizations weren’t looking. The research found leaders reporting significant ROI in areas like auditing customer interactions (31% of leaders versus 19% of others) and automating routine tasks and administration (47% versus 18%), alongside the more easily predicted gains in sales forecasting and customer service. “Keep your options open because you have no idea what kind of benefits AI is going to have once it’s in play,” Reynolds said. “It could affect areas in completely different departments or different regions.”  

The findings make it clear that thinking of CX as a standalone technology stack is an outdated point of view. The organizations unlocking the most value from AI aren’t treating CX as a front-office bolt-on function; they’re operating in environments where CX and the systems that run the business—ERP, supply chain, finance—share the same foundation. 

The research covered 10 industries evenly. While the specifics of integration vary across them, one pattern held: harmonized infrastructure and workforce investment separated the leaders from everyone else.  

Organizations that have already built that foundation face a specific question: whether or not to let AI work within what components of their technology foundation are already interconnected. The performance gap in this research suggests that most haven’t yet achieved this depth of implementation. But the leaders who have—pairing harmonization and workforce readiness with AI that orchestrates across functions—are the ones whose results everyone else is still trying to pilot their way toward.